"Information or resources about playwrights or the Playwright framework" matching MCP servers:

An MCP server for running Playwright tests and reading structured results, failed test details, and attachment content, designed for AI agents doing test failure analysis.

Enables syncing Playwright, Allure, and JUnit test results into existing Kiwi TCMS test executions, with dry-run safety, automatic failure comments and attachments, and guarded raw RPC access.

An MCP server that unpacks and structures Playwright trace.zip archives so AI agents can perform root-cause analysis on CI failures, with 16 focused tools for inspection, DOM/UI analysis, root-cause analysis, and performance analysis.

Enables agents to run Playwright suites, diagnose failures from trace-level DOM, network and console evidence, and apply locator fixes that are re-run and reverted if still red. It also repeats failing tests for per-test flaky, regressed or broken verdicts and surfaces the same diagnosis and fix diffs in CI job summaries and PRs.

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A LangGraph-powered MCP server for infrastructure orchestration with autonomous subagents.

Local MCP decision gate for AI agents and CI/CD: check candidate actions against owner-controlled policy and proposal-bound evidence. Three read-only tools report admissible options, missing evidence, and SHA-256 receipts. No selection, execution, or DeltaX API key.

Mneme exposes a governed Decision Index so MCP clients can propose candidate architectural decisions and query decision state, applicability, and traceability. Proposals remain non-authoritative: accepting or activating protections stays under explicit human control.

Fail-closed merge gate for AI coding agents: verify_repo runs the tests that existed before the change against a git working tree and answers MERGE, BLOCK or INCONCLUSIVE. The agent names what to judge; the operator pins the baseline and the floors.

Enables AI coding agents and CI to vet npm dependencies before they reach the lockfile, flagging hallucinated, slopsquatted, or otherwise risky packages with evidence-backed verdicts.

Generates a daily standup note from GitLab merge request or GitHub pull request state: what is ready to merge, what is blocked, what is stale, and what is waiting on your review. When CI is red it opens the failed job's log and reports the error lines, so the note says why the pipeline failed rather than just that it did.

Enables AI coding tools to scaffold, build, and deploy Node.js or Python apps to Varity with a single command, automatically provisioning databases and backend services.

MCP server for publishing HTML or Markdown to a live hosted URL via htmldrop. Provides tools to publish, list, and delete hosted sites, with remote OAuth and API token authentication.

Enables AI assistants to summarize Playwright test runs, identify flaky tests, heuristically triage failures, generate Playwright test stubs, and retrieve recent GitHub CI status through MCP tool calls.

Provides MCP tools to get a single-call snapshot of git and GitHub Actions CI status across all repositories in a folder, flag missing or stale architecture docs, write doc files, and detect release drift between source and release repositories.

Enables AI coding tools to validate local projects and publish or update applications to Bedengan App Hub via API, with automated checks and live deployment without manual approval.

SSWP MCP — Deterministic software attestation for AI-augmented development. Witness any repo through a 5-gate pipeline, adversarially probe dependencies, and produce self-verifying .sswp.json attestations. Fleet registry across 131 nodes with tamper-proof audit ledger and FTS5 search. Agent-native — one tool call from Hermes, Claude, or Cline.

Enables AI clients to assess infrastructure-as-code deployment risk, generate incident response runbooks, review CI/CD delivery readiness, and calculate SLO error budgets through structured advisory tools. Runs locally over stdio without cloud credentials or external API calls, returning guidance for platform work, pull request review, and production readiness checks.

Detects breaking changes in a TypeScript library's public API and recommends the semver bump, comparing two npm releases, git refs or a working tree. Each finding is graded proven or review-only.

An MCP server that enables AI assistants to discover and execute Nox sessions for project automation tasks like testing, linting, and building. It provides tools to list available sessions and run them using specific Python versions, tags, or keyword expressions.

Stops your AI from re-introducing bugs, leaking provider keys, or weakening tests. Bug fixes become permanent regression guards; blocked mistakes become AI lessons the agent reads and learns from before its next edit.

Deploy, run and manage apps on your own self-hosted AppCrane from any MCP client. 62 tools: create an app, push code, deploy to sandbox, check health and logs, provision a managed Postgres, MariaDB, MongoDB or Redis, and promote to production after review. Your instance, your SSO, your data. Repo: https://github.com/gitayg/appcrane-mcp · npm: appcrane-mcp · Site: https://appcrane.dev

Enables AI coding agents to compute a 0-1 diff risk score for the current branch or any pull request, exposing the driving signals, evidence, tier and resulting auto-approve or human-review policy decision. Agents can use it to decide whether a low-blast-radius, AI-reviewed PR is safe to merge automatically while flagging risky changes for a human.

Enables code-review gating by converting a git diff into a typed verdict with safety probabilities, severity, and recommended actions for auto-merge or human review.

Deploys and manages projects on Swigs Cloud from any MCP client, turning folders or git repositories into live HTTPS sites in about two minutes.

An MCP server that lets AI assistants manage KubeAid GitOps clusters, inspecting ArgoCD apps, pods, events, and resources, with optional write operations like syncing apps and scaling deployments through your own kubeconfig credentials.

Compacts noisy test, build, and cloud-log output before an AI agent reads it — dedupes repeats, collapses stack frames, folds Playwright retries, and renders CloudWatch/GCP JSON logs down to the signal. Typically 80–95% fewer tokens on failures. Tool: compact_output. Run: npx -y logslim logslim-mcp

Enables AI coding agents to see their Odoo.sh projects by listing projects, branches and builds, waiting for a build to finish, reading build and server logs, and optionally rebuilding branches or updating the firewall. It runs read-only by default with bounded, time-limited tool calls, keeping the user's Odoo.sh session out of the agent's reach.

Enables deployment and management of applications on the Citizen platform from git repositories or local files. It allows AI assistants to monitor deployment logs, handle authentication, and automatically fix build errors using intelligent error analysis.

Enables coding agents to upload local .apk or .ipa builds and receive tester install links without leaving the editor.